Image-based digital control of plasma processing

ABSTRACT

A system and method including a processing device. The processing device receives data including a first set of plasma exposure values each associated with a respective plasma element of a plurality of plasma elements designed to generate plasma related fluxes. The processing device causes a plasma controller to activate the set of plasma elements based on the data to expose a substrate to the plasma related fluxes generated by the set of plasma elements during a plasma process. Each respective plasma element of the set of plasma elements is activated for a duration based on a respective plasma exposure value from the first plurality of plasma exposure values that is associated with the respective plasma element.

TECHNICAL FIELD

Some embodiments of the disclosure relate, in general, to digitalcontrol of plasma processing. Embodiments additionally relate tosystems, device, and methods for plasma delivery and/or plasmaprocessing.

BACKGROUND

Plasma processing is widely used in the semiconductor industry. Plasmacan modify a chemistry of a processing gas (e.g., generating ions,radicals, etc.), creating new species, without limitations related tothe process temperature, generating a flux of ions to the wafer withenergies from a small fraction of an electronvolt (eV) to thousands ofeVs. There are many kinds of plasma sources (e.g., capacitively coupledplasma (CCP), inductively coupled plasma (ICP), microwave generatedplasma, electron cyclotron resonance (ECR), and the like) that cover awide operational process range from a few mTorr to a few Torr.

A common plasma process specification today is a high uniformity of theprocess result (e.g., a uniformity across a wafer up to the very edge ofthe wafer). This standard is often very difficult to achieve, because itinvolves many factors, many of which interfere with others. Plasmauniformity, chamber design, wafer temperature distribution, design ofthe bias electrode, etc. are only part of those factors. To satisfythese criteria, one designs both RF antennas and processing chambers toachieve the highest level of process uniformity. This often leads tolarge dimensions of a chamber and power generators (e.g., antennas,coils, electrodes, etc.), large overall plasma volume, and otherexpensive measures, like complex temperature control, coil splittingmagnetic field screens, etc. While basic process uniformity within a fewpercent can be fixed by a general tool design, even these measures areoften inadequate, when uniformity criteria become stricter. A chamberthen has to be equipped with elements that can allow individual tuningof the chamber for specific processes. In addition, large plasma volumeby itself may be a problem for processes that require quick change ofchemistry.

One can observe a parallel between plasma processing and TV. OriginallyTV was based on Cathode Ray Tube (CRT) technology, where an electronbeam scans horizontally and vertically inside a vacuum tube excitingphosphor dots on the front panel of the tube, making about 25 frames persecond. Each phosphor dot flashes light for a short (fixed) time and thebrightness of this flash is controlled by the electron beam current.Then a receptor (e.g., an eye) integrates for a brief time duration andaverages the brightness of light coming from every phosphor dot. Thecolor of the dot is determined by the ratio of average brightness ofneighboring color dots and the brightness is by an overall intensity ofthe light from these dots. The analog nature of CRT image control is inthe control of intensity of the electron beam, or in the peak brightnessof every light flash. CRT and other analog systems reveal challenges ofmaintaining specific process specification (e.g., power requirements,chamber size, element specification limitation, etc.) due to the strictspecification requirements to perform the process. Like CRT, analogsystems generally often lack the flexibility demanded by moderninnovation in various fields of process control. For this reason analogsystem are often manufactured with a specialized specification toperform a specific narrow range of processes.

Growing problems with CRT technology were resolved by switching to adigital technology, which of course required changing both the hardware,the signal and the signal control. Apparently, to switch analogtechnology to a digital one in plasma processing, one will have tochange both—hardware and control.

SUMMARY

In an example embodiment, a method includes receiving, by a processingdevice, data including a first set of plasma exposure values eachassociated with a respective plasma element of a plurality of plasmaelements designed to generate plasma related fluxes. The processingdevice causes a plasma controller to activate the set of plasma elementsbased on the data to expose a substrate to the plasma related fluxesgenerated by the set of plasma elements during a plasma process. Eachrespective plasma element of the set of plasma elements is activated fora duration based on a respective plasma exposure value from the firstplurality of plasma exposure values that is associated with therespective plasma element.

In an example embodiment, a method includes receiving, by a processingdevice, first data including a first set of plasma exposure durationseach associated with a respective plasma element of a set of plasmaelements designed to generate plasma related fluxes. The processingdevice receives a first thickness profile of a substrate. The firstthickness profile includes a first set of thickness values of the firstsubstrate measured after exposing the first substrate to the plasmarelated fluxes for the respective plasma exposure durations defined inthe first data. The processing device determines that the firstthickness value includes a first thickness value for a first location onthe first substrate associated with a first plasma element of theplurality of plasma elements that deviates from a reference thicknessvalue. The processing device, responsive to determining that the firstthickness profile includes the first thickness value that deviates fromthe reference thickness value, modifies the first data by changing afirst plasma exposure duration of the plurality of plasma exposuredurations that is associated with the first plasma element.

In an example embodiment, a plasma processing system includes aprocessing chamber and an actuator plate disposed within the processingchamber. The actuator plate includes a set of plasma cells. The plasmaprocessing system further includes a control unit coupled to theactuator plate, the control unit is to control the actuator plate byindependent activation or deactivation of the plurality of plasma cells.Responsive to being activated the plasma cells are to independentlyexpose a local area of a substrate disposed within the process chamberto plasma related fluxes.

In an example embodiment, a system includes a processing chamber and anactuator plate disposed within the processing chamber. The actuatorplate includes a set of plasma elements to independently expose asubstrate disposed within the processing chamber to plasma relatedfluxes. The actuator plate is to independently activate the plurality ofplasma elements. Responsive to being activated, a plasma element is toindependently expose a local area of the substrate to the plasma relatedfluxes. The actuator plate is to perform individual time-dependentactivation of the plurality of plasma element to selectively expose thesubstrate to the plasma related fluxes. In an example embodiment, aplasma processing device includes a plasma source to generate a plasma.The plasma processing device further includes an actuator plate disposedin a path of the plasma. The actuator plate includes a plurality ofplasma elements to independently be activated and deactivated.Responsive to being activated the plasma elements expose a substrate tothe plasma related fluxes. The plasma processing device further includesa control unit. The control unit controls the actuator plate. Thecontrol unit perform individual time-dependent activation of theplurality of plasma element to selectively expose the substrate to theplasma related fluxes.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure is illustrated by way of example, and not by way oflimitation, in the figures of the accompanying drawings in which likereferences indicate similar elements. It should be noted that differentreferences to “an” or “one” embodiment in this disclosure are notnecessarily to the same embodiment, and such references mean at leastone.

FIGS. 1A-C illustrate digital imaging used in a digital process controlsystem, according to aspects of the disclosure.

FIG. 2A-C illustrate embodiments of a plasma processing system,according to aspects of the disclosure.

FIGS. 3A-B illustrate digitally controlled plasma elements, according toaspects of the disclosure.

FIGS. 4A-B illustrate addressable plasma elements, according to aspectsof the disclosure.

FIG. 5 illustrates a digital process control system, according toaspects of the disclosure.

FIG. 6A-E illustrates various processing images, according to aspects ofthe disclosure

FIG. 7A-C illustrate a digitally controlled plasma processing device,according to aspects of the disclosure

FIG. 8 is a flow chart of a method for plasma delivery, according toaspects of the disclosure.

FIG. 9 is a flow chart of a method for tuning a plasma process,according to aspects of the disclosure.

FIG. 10 is a flow chart of a method for tuning a plasma process,according to aspects of the disclosure.

FIG. 11 is an exemplary illustration of a training phase of a machinelearning model, according to aspects of the disclosure.

FIG. 12 is a flow chart of a method of using a machine learning model tomodify a plasma exposure process, according to aspects of thedisclosure.

FIG. 13 depicts a block diagram of an example computing device capableof plasma delivery and/or processing, operating in accordance with oneor more aspects of the disclosure.

DETAILED DESCRIPTION

A common plasma process parameter today is a high uniformity of aprocess result (e.g., a uniformity across a wafer up to the very edge ofthe wafer). This parameter is often very difficult to achieve, becauseit involves many factors, many of which interfere with others. Plasmauniformity, chamber design, wafer temperature distribution, design ofthe bias electrode, etc. are only part of those factors. Radio frequency(RF) antennas and processing chambers are manufactured and assembled toachieve the highest level of process uniformity. This often leads tolarge dimensions of a chamber and power generators (e.g., antennas,coils, electrodes, etc.), large overall plasma volume, and otherexpensive measures, like complex temperature control, coil splitting,magnetic field screens, etc. While basic process uniformity within a fewpercent can be fixed by a general tool design, even these measures areinadequate for stricter uniformity criteria. A chamber then has to beequipped with elements that can allow individual tuning of the chamberfor specific processes. In addition, large plasma volume, by itself, maybe a problem for processes that require quick change of chemistry.

In addition, difficulties exist within process development to satisfyboth local process results (e.g., film properties, etc.) and uniformitycriteria. When a process tool is manufactured, conventionally it istested and optimized for just a few processes. As more processes aredeveloped, the conventional tool has limited means to control processresults, such as by controlling power in antennas, gas pressure, gasflow, gas flow distribution, temperature of a wafer, chamber walls, andthe like. Many of these control knobs affect multiple plasma parameterswhich is often difficult to predict, because they have global influence.For example, changing power in one coil may affect the plasma densityeverywhere, may affect the ion energy, etc. These difficulties and theabsence of a clear (not ambiguous) way for using these knobs result in avery high cost of process development, which sometimes may call forhardware modification and re-qualification of the tool.

These problems can be mitigated, and in some cases eliminated if ananalog process control is replaced with a digital process control. As wementioned above, replacing an analog process control with a digitalprocess control would likely require different hardware. The maindifference between hardware for analog and digital systems is thatanalog systems often have very few elements (1—2 coils; 1—2 zone ESC, .. . ) and, respectively, very few controlling elements to controlparameters globally, while digital systems are often configured forlocal control of small areas of the wafer and thus normally should havea lot of identical controlled elements/cells (e.g. 200-1000 zones ESC,etc.) and appropriately a large number of controlling elements. Contraryto analog systems, where those few elements operate for the same time,but energized to carefully adjusted/controlled levels, in a digitallycontrolled system one energize/activate every cell (e.g., pixel) to thesame level (e.g. powered), however, the exposure time of each cell maybe controlled. The dependency between process parameters (e.g.,thickness) and input parameters (e.g. cell exposure duration) isstreamlined allowing a user or process recipes to alter or changeparameters without performing an equipment overhaul or massrestructuring. Digital control also allows for a consistent power inputacross exposure sources often resulting in simpler electronicconfigurations and equipment setups capable of performing multipleprocesses.

To better understand how the digital process control can be realized, wedraw a comparison between analog system and digital system. Indeed, inplasma processing the process result on the film (removal, ordeposition, or treatment) grows with time and flux of the plasma speciesto the substrate. So if one needs to increase process result globally orlocally, one needs to increase flux or time. In the end, it is thefluence (integral of the flux density over time) that affects theresulting process image. For example, in TV imaging—the brightness orcolor of each pixel that the eye sees depends on the average brightnessof this pixel over about 0.1 s, or the fluence of photons in that time.In CRT, every pixel emitted light for the same time, so one variedbrightness over the screen by changing the flux density (electron beamcurrent illuminating the pixel). In digital processing (independent oftechnology) each pixel emits light with fixed intensity, and the averagebrightness of every individual pixel during one frame (fluence over theframe) can be controlled by the fraction of a timeframe that that pixelis lit. Typical grey scale of any color pixel in digital TV can be 256or 512 grey levels, which allows for millions of colors. This grey scaleand its consistency can be achieved by splitting every frame (image)into a set of subframes, each subframe shows a different image for atime (sustain period) assigned for this subframe, and during allsubframes illuminated pixels can emit light of the same fixed intensity.However, some pixels are lit during one subframe and others are litduring other subframes. Different combination of pixels may be lit forany number of subframes. The human eye is not fast enough to recognizeeach subframe. The human eye sees the integral image of a severalframes, or the image of a fluence of light from every pixel. Forexample, for 8 subframes, realizing 256 levels of intensity, the timefor each subframe can depend on the subframe number m as 2^(m-1), so thecontribution of each subframe to overall fluence of the frame increaseswith the subframe number, so the average brightness (fluence) of everypixel may have 256 variation from 0 to 255.

The example below shows an example of the splitting one 3×3 image (wherethe numbers are indicative of a brightness level) into a number ofsubframe images, assuming that each subframe is twice as long as theprevious, so its contribution to the brightness grows as 2^(m-1):

$\overset{\begin{matrix}Z_{1} & Z_{2} & Z_{3}\end{matrix}}{\begin{matrix}Y_{1} \\Y_{2} \\Y_{3}\end{matrix}\underset{Image}{\begin{pmatrix}1 & 2 & 3 \\0 & 2 & 1 \\2 & 0 & 4\end{pmatrix}}} = {\underset{SFlast}{\underset{{SF}\; 1}{\begin{pmatrix}1 & 0 & 1 \\0 & 0 & 1 \\0 & 0 & 0\end{pmatrix}}} + \underset{{SF}\; 2}{\begin{pmatrix}0 & 1 & 1 \\0 & 1 & 0 \\1 & 0 & 0\end{pmatrix}} + \underset{{SF}\; 3}{\begin{pmatrix}0 & 0 & 0 \\0 & 0 & 0 \\0 & 0 & 1\end{pmatrix}} + \begin{pmatrix}0 & 0 & 0 \\0 & 0 & 0 \\0 & 0 & 0\end{pmatrix} + \ldots + \underset{{SF}\; 4}{\begin{pmatrix}0 & 0 & 0 \\0 & 0 & 0 \\0 & 0 & 0\end{pmatrix}}}$

In order to have different images for every subframe, each subframe caninclude an address period preceding a sustain period. The address periodmay include erasing the previous image and placing a new image on thescreen. This updating of the address may include an addressable memoryelement assigned to each pixel, which can be addressed to ON or OFFstate. The ON or OFF state may affect pixel operation (e.g. to emitlight or not) during the sustain period. Addressing may includecircuitry for selecting pixels and supply them with address signal tocarry out the addressing process.

In some embodiments, methodology include splitting the process time intoa number of subfields and controlling fluence of plasma fluxes toelements of the substrate with time, rather than with flux density, asconventionally used for plasma processing. In some embodiments,methodology is used for selecting and quick addressing of thousands ofplasma cells, which drastically reduces the number of controllingelements compared to a number of controlled elements.

Embodiments of the disclosure provide for plasma processing devices,methods, and systems using digital process control. Specifically,embodiments disclosed herein are directed to devices, systems, andprocesses for controlling a plasma process through individual timedependent exposure of plasma related fluxes by plasma elements.Embodiments are directed to performing plasma processes (e.g.,semiconductor processing) by digitally controlling a local exposure ofthe elements of the substrate to plasma related fluxes. Embodiments aredirected to generating and processing exposure data (e.g., exposure mapsor exposure recipes) across a set of plasma elements to individuallycontrol exposure durations corresponding to individual plasma elements.Various embodiments may include or employ methods for tuning and/orrefining exposure data (e.g., exposure maps or recipes). Someembodiments incorporate the use of machine learning models andalgorithms to generate, modify, and/or process exposure maps and/orrecipes and plasma process modifications to achieve target processoutputs (e.g., meet target specifications such as thickness and/orprocess uniformity).

In an example embodiment, a method includes receiving, by a processingdevice, data including a first set of plasma exposure values eachassociated with a respective plasma element of a plurality of plasmaelements designed to generate plasma related fluxes. The processingdevice causes a plasma controller to activate the set of plasma elementsbased on the data to expose a substrate to the plasma related fluxesgenerated by the set of plasma elements during a plasma process. Eachrespective plasma element of the set of plasma elements is activated fora duration based on a respective plasma exposure value from the firstplurality of plasma exposure values that is associated with therespective plasma element.

In an example embodiment, a method includes receiving, by a processingdevice, first data including a first set of plasma exposure durationseach associated with a respective plasma element of a set of plasmaelement designed to generate plasma related fluxes. The processingdevice receives a first film thickness (process result) profile of asubstrate. The first thickness profile includes a first set of thicknessvalues of the first substrate measured after exposing the firstsubstrate to the plasma related fluxes for the respective plasmaexposure durations defined in the first data. The processing devicedetermines that the first thickness value includes a first thicknessvalue for a first location on the first substrate associated with afirst plasma element of the plurality of plasma elements that deviatesfrom a reference thickness value. The processing device, responsive todetermining that the first thickness profile includes the firstthickness value that deviates from the reference thickness value,modifies the first data by changing a first plasma exposure duration ofthe plurality of plasma exposure durations that is associated with thefirst plasma element.

In an example embodiment, a plasma processing system includes aprocessing chamber and an actuator plate disposed within the processingchamber. The actuator plate includes a set of plasma cells. The plasmaprocessing system further includes a control unit coupled to theactuator plate, the control unit is to control the actuator plate byindependent activation or deactivation of the plurality of plasma cells.Responsive to being activated the plasma cells are to independentlyexpose a local area of a substrate disposed within the process chamberto plasma related fluxes.

In an example embodiment, a system includes a processing chamber and anactuator plate disposed within the processing chamber. The actuatorplate includes a set of plasma elements to independently expose asubstrate disposed within the processing chamber to plasma relatedfluxes. The actuator plate is to independently activate the plurality ofplasma elements. Responsive to being activated, a plasma element is toindependently expose a local area of the substrate to the plasma relatedfluxes. The actuator plate is to perform individual time-dependentactivation of the plurality of plasma element to selectively expose thesubstrate to the plasma related fluxes. In an example embodiment, aplasma processing device includes a plasma source to generate a plasma.The plasma processing device further includes an actuator plate disposedin a path of the plasma. The actuator plate includes a plurality ofplasma elements to independently be activated and deactivated.Responsive to being activated the plasma elements expose a substrate tothe plasma related fluxes. The plasma processing device further includesa control unit. The control unit controls the actuator plate. Thecontrol unit performs individual time-dependent activation of theplurality of plasma element to selectively expose the substrate to theplasma related fluxes.

These and similar embodiments provide a number of advantages andimprovements in the fields of plasma processing and semiconductorprocessing. These advantages include, for example, improved processprecision, improved process resolution, increased flexibility ofequipment specification and process use. As noted previously,conventional global process controls that use analog system presentdifficulties meeting uniformity requirements. By using a digital localprocess control system, or time dependent local exposure control, thecontrol parameters are much easier to adjust for different processes ortarget outcomes. Additionally, the level of precision and resolution canbe adjusted by adjusting exposure instructions for a digital processcontrol system. For example, process distortions, process artifacts,limitations on size and shape of equipment are overcome when the processcontrol is time dependent instead of power dependent, like most analogprocess control system. Resolution can be controlled by the number ofprocess sources without major peripheral equipment changes or changes torelative process uniformity.

As mentioned previously, using a digital process control allows for moreflexible system control. The dependency between process resultparameters (e.g., film thickness change) and input parameters (e.g. cellexposure duration) is streamlined allowing an operator to adjust theprocess recipe (multiple exposure times) without requiring an equipmentoverhaul or restructuring. Digital control also allows for a consistentpower input across exposure sources often resulting is simpler, cheaper,and broader use electronic configurations and equipment setups capableof performing multiple processes.

FIGS. 1A-1C illustrates digital imaging used in a digital processcontrol system 100A, according to aspects of the disclosure.Particularly, FIG. 1A illustrates a principle of creating an image (e.g.a collection of image frames 102) using subframes 104A-H as well asscanning techniques for addressing controlled elements 106 of thedigital process control system 100A. Plasma processing can operate witha large number of controlled elements 106 (e.g. pixels, cells,electrodes, etc.) that emit light or plasma, control plasma fluxes, etc.For example, plasma processing systems may operate with hundreds orthousands of plasma cells. In any case, a large number of controlledelements 106 can require a high degree of control to carry out thedigital process to meet a desired output standard (e.g. processuniformity requirements). For example, as shown in FIG. 1A, every frame102 (e.g. 16.7 msec for TV) can be divided into a series of subframes104A-G (e.g. 8 subframes as seen in FIG. 1A). Each subframe can berepresentative of a duration of controlled element 106 activation(sustain) periods, growing with the subfield number m asT_(m)=T₁2^(m-1).

Each sustain period can be preceded by an address period. The addressperiod includes erasing (e.g. OFF state) the previous state of all ofthe controlled elements 106 and addressing (e.g. ON state) a newselection of controlled elements 106. During the following sustainperiod, all elements that were selected ON are activated (e.g. emitlight or plasma) of the fixed intensity. The emission duration by thepixels results in various levels of fluence. Different combinations ofaddressed controlled elements 106 of different subfields 104A-G of aframe 102 can be used to generate different exposure images. Forexample, controlled elements 106 having light emitting pixels can resultin a fluence (e.g. brightness) with various level of grey (e.g. 256levels of grey associated with the 8 subfields). This is due, in part,to the human eye integrating (i.e. summarizing) light from every pixelreceived during a selection of frames (e.g. integrating over thesubfields). For example, if a pixel with coordinates (y, z) equal to (6,2) emits a relative brightness of level 3, pixel (9, 5)—level 162, andpixel (9, 9)—level 104, then these pixels should be addressed ON forappropriate subframes that when summarized (e.g. integrated over theduration) result in the associated brightness levels (i.e. 3, 162, and104), as shown in the FIG. 1A.

In some embodiments, improved addressing efficiency (e.g. shorter timeto address the pixels) can be achieved through address scanning.Scanning is performed during an addressing period by disconnecting (e.g.connecting to ground) all lines along a first axis (e.g. horizontallines 108) except one from a power supply (e.g. Y scan electrode 110).The first line is addressed, while the disconnected lines cannot beaddressed (e.g. store or change charge) from an addressing signal. Theaddressing process carries on line by line where the line of controlledelements 106 (e.g. pixels or cells) connected to a power supply arebeing addressed. After a current line is addressed, the current line isdisconnected from the power supply (e.g. Y scan electrode 110) and thenext line is connected to it. After all lines are scanned, the addressperiod ends and the sustain period begins. For example, FIG. 1A showsaddressing of line 108 number 9 for the subframe SF6 104F. As shown inthe FIG. 1A, the selected electrodes 3, 5, 6, 7, 9 and 10 are connectedto address electrode Z 112. These selected electrodes on line 9 will beaddressed and ultimately be lit during the processing of the SF6subframe 104F.

Using a previous example (repeated below), an image can be representedby a 3×3 matrix, where each number is indicative of an emission durationof a controlled element. An exemplary splitting of 3×3 image into anumber of subframe images can include the following:

$\overset{\begin{matrix}Z_{1} & Z_{2} & Z_{3}\end{matrix}}{\begin{matrix}Y_{1} \\Y_{2} \\Y_{3}\end{matrix}\underset{Image}{\begin{pmatrix}1 & 2 & 3 \\0 & 2 & 1 \\2 & 0 & 4\end{pmatrix}}} = {\underset{SFlast}{\underset{{SF}\; 1}{\begin{pmatrix}1 & 0 & 1 \\0 & 0 & 1 \\0 & 0 & 0\end{pmatrix}}} + \underset{{SF}\; 2}{\begin{pmatrix}0 & 1 & 1 \\0 & 1 & 0 \\1 & 0 & 0\end{pmatrix}} + \underset{{SF}\; 3}{\begin{pmatrix}0 & 0 & 0 \\0 & 0 & 0 \\0 & 0 & 1\end{pmatrix}} + \begin{pmatrix}0 & 0 & 0 \\0 & 0 & 0 \\0 & 0 & 0\end{pmatrix} + \ldots + \underset{{SF}\; 4}{\begin{pmatrix}0 & 0 & 0 \\0 & 0 & 0 \\0 & 0 & 0\end{pmatrix}}}$

In this example, the scanning during SF1 can proceed in the followingmanner: 1) when Y1 is closed (e.g. connected to the power supply), theaddress signal (1, 0, 1) connects the first and third columns to theaddress driver; 2) when Y2 is closed, the address signal (0, 0, 1)connects the third column (e.g. Z3) to the address driver; and 3) whenY3 is closed, none of the Z electrodes is connected to Z driver. Asimilar process occurs for each addressing period for each subfield. Insome embodiments, some subfield may not active (e.g. all elements in OFFstate) any of the elements. Returning to the above example, startingfrom SF4, none of Z electrodes is connected to Z driver, thus no cell isaddressed and no controlled elements are activated (e.g. no light orplasma is generated during these subfields).

During the sustain period all scan (line) electrodes (Y) can beconnected together and to a power supply. Column electrodes (Z or X) areconnected together and to a sustain driver of the power supply. In someembodiments, Z and X use the same electrodes in the cells, however, inother embodiments X is a separate electrode, common to every cell. Whileduring the sustain period all cells are connected to the same sustaindrivers, only cells selected ON during address period are activated(e.g. emit light or plasma).

A difference between digital TV and digital plasma processing is thatdigital TV can require a maximum frame duration limit to meet imagequality standards. For example, TV frames are limited to being shorterthan 0.1 s for viewing not to be disturbed by flickering, even of astatic image, and about 6 times shorter (16.7 ms) to avoid movingpicture artifacts. As a result, TV images are often shown through many16.7 ms frames, as shown in FIG. 1B, for example. This requires a largenumber of addressing, which takes significant fraction of 16.7 ms frame,reducing light efficiency of the TV image.

In some embodiments, as shown in FIG. 1C, the whole process time orprocess step time may be performed as a single frame 100C (e.g.addressing a single frame). Using a single frame may be enabled as aresult of not having a maximum frame duration limitation, as previouslydescribed in relation to a TV display. For example, the addressing timefor each frame can be about a millisecond in duration and process timecan be measured in many seconds or even minutes. The longer processingtimes can result in fewer addressing steps, which can improve theefficiency of the overall process.

In some embodiments, as shown in FIG. 1C, varying frame duration may beassociated with image complexity. For example, a TV image can berelatively complex, so pixels may have the full range of brightness from0 to 255. However, in plasma processing, the main image has a constantbrightness (e.g. no contrast), and the resulting process result maysatisfy a quality threshold that is not as precise as a TV image (e.g.5% non-uniformity). As a result of this reduced image complexityrequirement, one large subframe may be used for a bulk of the time (e.g.90% of total process time) and a few smaller subfields (e.g. 6subfields, as shown in FIG. 1C), may be used for the remaining processtime (e.g. 10% of total process time).

In some embodiments, the subfields can be changed by a shared adjustmentfactor (e.g. all subfield are reduced by half). In some embodiments,using longer subfields can result in increased precision control byreducing the number of required subfields. For example, with 8subfields, brightness can be controlled up to 0.4% (1/255) of the totalbrightness. However, using longer subfield brightness can be controlledup to 0.15% (1/663) of the total brightness with only 7 subfields.

In some embodiments, plasma cells used for plasma processing are able tocontrol plasma fluxes in multiple conditions (e.g. different processinggases, different pressures, etc.) and control emitted energy (e.g. ionenergy, bias voltage), which may require different driving voltages fordifferent process steps. The uniformity control of every process can beperformed using the digital control described herein.

In some embodiments, the number of subfields, the relative length ofsubfields, the number of frames processes, and/or process length can beadjusted to meet the requirement of a plasma process (e.g. a fabricationrecipe). For example, the sustain and address voltage/signals can bemodified and new gas mixtures can be introduced providing process recipeflexibility.

FIGS. 2A-C illustrate embodiments of a plasma processing system 200,according to aspects of the disclosure. The plasma processing system mayinclude a processing chamber 220 and a plasma source 210. A plasmasource comprises walls 202 (e.g. to hold the atmospheric pressure), agas inlet 212, the gas distribution volume limited by the walls, theplasma generating plate 204, containing multiple controlled plasma cells206, and the power supply 208 controlled by the control unit 205. Insome embodiments, control unit 205 is also responsible for selection ofplasma elements 206 which generate plasma when the same voltage V(t) isapplied to all cells of the panel 204. The processing chamber 220 may beone or more of an etch chamber, a deposition chamber (including achamber for atomic layer etch/deposition, chemical vapor deposition,physical vapor deposition, or plasma enhanced versions thereof), ananneal chamber, a photoresist strip chamber and/or the like. Processingchamber 220 includes walls 211 that holds inside vacuum and providessupport to the plasma source 210, substrate support 216, and gas outlet214 and may include features described in association with processingchambers in other embodiments. The gas inlet 212 and gas outlet 214 mayprovide a flow of feed gas through the processing system under theprocessing gas pressure. The feed gas may be comprise any of air, O2,N2, Ar, NH3, He and or other appropriate processing gases. Plasma source210 may include a gas expansion volume of a gas injector (e.g. withoutplasma) which provides a uniform gas flow through plasma generatingplate 204. The uniform gas flow across the surface of the control platemay result in a common gas composition flowing through each of the gasfeed lines associated with the discharge cells 206.

In some embodiments, as shown in FIG. 2A, the plasma generating plate204 may include a set of plasma elements with memory. The plasmaelements 206 include individually addressable plasma sources ordischarge cells capable of emitting plasma related fluxes. For example,the discharge cells may use a dielectric barrier discharge (DBD)technology for both generating discharge and providing memory function.

In some embodiments, the discharge cells may be disposed within theplasma generating plate 204. The discharge cells may be designed toindividually switchable between an ON state and an OFF state. While inan ON state the discharge cells emit plasma related fluxes responsive toreceiving a voltage (e.g. a sustain voltage).

In some embodiments, the plasma generating plate 204 is designed tocoordinate individual time-dependent transitions between the on stateand the off state for each discharge cell to selectively generate andemit plasma related fluxes across the plasma generating plate 204. Forexample, plasma related fluxes may be generated and emitted to contact asubstrate 230 disposed within processing chamber 220.

In some embodiments, the plasma source 210 may include an RF (e.g., lowfrequencies less than 100 kHz) generator 208, or alternatively analternating current (AC) generator, that is designed to activate (e.g.,deliver power) to the discharge cells 206, and control unit that selectscells which are to receive the power from the generator. For example,discharge cells may include an addressable switch, which connects bothcell electrodes to the RF bus electrodes only when closed, anddisconnects the cell from the RF bus electrodes when the switch is open.Applying the RF voltage to an associated discharge cell results in theassociated discharge cell being in the ON state and emitting plasmarelated fluxes. In a further example, the RF generator may be configuredto apply an RF voltage to a first set of discharge cells for first timeduration and apply the same RF voltage to a second set for a differenttime duration. In another embodiment, the RF generator may be designedto increase or reduce a power to maintain a predetermined voltageindependent of the number of discharge cells being activated or in an ONstate and/or the number of discharge cells not currently activated or inan OFF state.

In some embodiments, which exploit DBD technology, the plasma source mayinclude a control unit that selects/addresses cells which receive amemory charge prior to plasma sustaining and an AC (1-200 kHz) powergenerator 208 with the fixed voltage amplitude designed to activate andsustain discharge in plasma elements (e.g. plasma cells) 206. Onlyselected plasma cells that have the memory charge will generatedischarge, when the same sustaining waveform V(t) is applied to allcells. Activated cells can generate plasma and emit plasma relatedfluxes to a local area in the area of this cell.

In some embodiments, as shown in FIG. 2B, the plasma generating plate204 is an actuator plate and is designed to perform individualtime-dependent opening and closing of the plurality of plasma shuttersto selectively expose regions of the substrate 230 to the ion andelectron fluxes flowing through the individual elements 206 of theactuator plate. This embodiment, of course includes a plasma source(shown ICP source) generating plasma above the actuator plate.

In some embodiments, the plasma elements 206 include multiple electrodelayers that perform the opening and closing that permits or blocks someof the plasma related fluxes from flowing through the activator plate.The plasma shutters 206 may include a first layer of electrodes (e.g.grid facing the plasma) disposed proximate and/or on a side of theplasma source 210. The first layer of the electrode may be maintained ata floating potential. The plasma shutters 206 may include a second layerof electrodes that includes a first ring of electrodes that aremaintained at a floating potential when an associated plasma shutter isopen and are maintained at a negative potential (reflects electrons)when the associated one of the plurality of plasma shutters is closed.The plasma shutter 206 may include a third layer of electrodes thatincludes ring electrodes to be maintained at the floating potential whenan associated plasma shutter is open and maintained at a positivepotential (e.g. reflects ions) when the associated plasma shutter isclosed.

In some embodiments, as shown in FIG. 2C, the plasma generating plate204 is an actuator plate buried in the pedestal and activates the plasmaelements 206. The plasma elements 206 may include multiple biaselectrodes to control fluence of high energy ions. Plasma is generatedby the plasma source 210 (ICP shown) and electrodes sustained by RFpower supply, which can supply an RF signal of the fixed amplitude. Thevoltage controller 205 may send the signal to the bias RF generatorduring the addressing period to modify power for any subframe accordingto a number (area) of activated electrodes, in order to provide the samebias voltage for all subframes, independent of the number of selectedelements.

In some embodiments, the number of plasma elements 206 is large and areaddressed by the control plate line by line (e.g., scanning) using(x_(i), y_(k)) or i, k coordinates, for example. The plasma elements 206may be individually addressed or addressed as a group or region, as willbe discussed in further embodiments.

FIGS. 3A-B illustrates a set of digitally controlled plasma elements300A-B, according to aspects of the disclosure. The set of controlledplasma elements 300A-B may be used in association with or as part of aplasma generating plate (e.g., plate 204 of FIGS. 2A-C). For example,the control may be applied to local plasma generation above adjacentelement of the substrate. In another example, the set of controlledplasma elements may be used in combination with a common plasma source(e.g., ICP), but the digital control of the plasma elements is used tocontrol the local fluence (integral of flux over time) of high energyions to a substrate. For example, the set of plasma elements may includesectional bias electrodes 302A-C. In an analog regime, fluence can becontrolled by changing voltage on each of these electrodes (e.g.changing fluxes or ion energy). In a digital regime, voltage remainssubstantially constant, but different times the bias is applied to eachsection to alter the fluence. For example, instead of having just a fewzones, bias electrode can be pixelated into many (hundreds) smallelectrodes. The electrodes can be associated (e.g. connected) into a fewzones as in previous example 304A-C, and achieve the same result, orcontrol each one of these small electrodes and achieve improvedflexibility and control of the process.

The time that the RF voltage (e.g. RF bias voltage) is applied to eachelectrode or each section of electrodes can be controlled. It should benoted that the applied voltage to each electrode can be independent ofthe number of active (e.g., ON state) electrodes. In some embodiments,to achieve independent applied voltage, the RF generator 208 may operatein a fixed output voltage mode. If a generator operates in the powercontrol mode, one can supply the RF generator a signal from the controlunit to adjust power according to the number of active electrodes.

The time required for driving each of the multiple discharge elementsmay be calculated and stored in an exposure duration map file (e.g. an“image” file). For example, for the case shown in FIGS. 3A-3B with only3 zones, the exposure file may include (t(a), t(b), t(c)) representingthe exposure duration for each zone. The following is an exemplarymethod realizing the exposure file for a system with three zones, aspreviously introduced. Suppose t(a)<t(b)<t(c). The whole panel (all 3zones) operates for the duration t(a), then zone A is turned OFF andonly zones B and C operate for duration of t(b)−t(a), then zone B isturn OFF and only zone C operates for the remaining time t(c)−t(b).Three zones process control allows to achieve a process profile withgood radial uniformity. The three sections 302A-C or zones allow formitigating center-low, center-high, or M-shape and W-shape radialprofiles on the substrate. When requirements to the process results isstricter (no local highs/lows, azimuthal uniformity) the necessarynumber of controlled elements is large, and this simple operation is notefficient. In this case, digital control methodology as presented hereincan provide a way of realization. In some embodiments, every element canoperate the same way (e.g. same emission rate of plasma related fluxes),but for appropriate time (e.g. exposure duration of the plasma relatedfluxes).

In some embodiments, while active (ON) discharge cells are connected tothe RF source, the inactive (OFF) cells may be grounded or float (i.e.not connected to anything). The plasma related fluxes to the wafer ofall species (e.g., ion, electrons, radicals, etc.) are independent onthe state of the discharge cells, except high energy ions. In someembodiments, the high energy ions may only be present above the active(on) electrodes.

Alternatively, the elements 304 may represent many plasma shutters (asin FIG. 2B). A plasma source that generates a plasma that emits plasmarelated fluxes may be disposed proximate the plasma shutters. Eachplasma shutter can be designed to switch between an open position and aclosed position. While in the open position a plasma shutter may permitthe ion and electron fluxes of the plasma to pass through the controlplate and while in the closed position the plasma shutters block theplasma related fluxes from passing through the control plate. Forexample, the plasma shutter may be individually addressed and controlledto selectively open and close to selectively expose a substrate to theplasma related fluxes flowing through the plasma shutters.

In some embodiments, the plasma shutters include multiple electrodelayers that perform the opening and closing that permits or blocks ionsand electrons from flowing through the plasma shutters (e.g. through acontrol plate). The plasma shutters may include a first layer ofelectrodes (e.g. grid facing the plasma) disposed proximate and/or on aside of the plasma source. The first layer of the electrode may bemaintained at floating potential. The plasma shutters may include asecond layer of electrodes that includes a first ring of electrodes thatare maintained at a floating potential when an associated plasma shutteris open and are maintained at a negative potential (reflects electrons)when the associated one of the plurality of plasma shutters is closed.The shutters may include a third layer of electrodes that includes ringelectrodes to be maintained at the floating potential when an associatedplasma shutter is open and maintained at a positive potential (reflectsions) when the associated plasma shutter is closed.

FIGS. 4A-B illustrates a set of addressable plasma elements 400A-B,according to aspects of the disclosure. The addressable plasma elementscan use dielectric barrier discharge (DBD) technology, which allowsindependent operation of each individual cell 402A-B (e.g.,mini-source), using selection capability (addressing) of a cell 402A-B(e.g., DBD cell). Alternatively, the addressable plasma elements caninclude individually addressable shutters, as discussed above. Anadvantage of dielectric barrier discharge is that a common voltagewaveform from a single power supply can be applied simultaneously to allcells 402A-B, but discharges will occur only in previously selected(addressed) cells, which can have natural memory capability withoutrequiring additional memory holding elements. The remaining cells 402A-Bwill be idle (no discharge). An alternating voltage (±V_(s)) atfrequency f from a power supply (e.g., AC generator 208 of FIG. 2) cangenerate a series of identical discharge pulses of the 2f frequency inthose selected cells. A discharge pulse can occur after every change ofpolarity, and the total amount of plasma related particles (ions,electrons, radicals) generated in any cell is proportional to the numberof pulses generated in that cell.

A combination of a few sub-images/subfields of different durations canbe used to generate exposure images (sum of sub-images). In someembodiments, exposure images include data having a set of exposureduration mapped to individual plasma elements. The plasma elements maybe oriented in a grid with individual activation instructions stored inan exposure image file. As will be discussed further in laterembodiments, an exposure image may include exposure duration values indifferent format (e.g. quantities of time, number of plasma pulses,etc.) that can be mapped to the cells 402A-B such that each cell 402A-Bpermits passage or generate plasma related element for an associatedexposure duration. In some embodiments, for each subfield, a controlunit (e.g. control unit 205 of FIG. 2) applies an appropriate sub-imageto a control plate (e.g. control plate 204) to address selected cells,which will then be active for the duration of that subfield.

As shown in FIGS. 4A-B, the cells may be disposed in an organizedstructure (e.g., a grid, a shape, etc.). Each cell 402A-B may be givenan address in two dimensional space (X,Y) or (Z,Y). The former uses 2electrodes structure, so both electrodes are used for both addressingand sustaining. The latter uses 3 electrodes, where additional electrodeis used together with Y (scan) electrode only for addressing, and X andY electrodes are used for sustaining discharge. Bothaddressing-sustaining schemes can be used to address the electrodes. Forexample, a cell may be assigned an address with an X address 404 (or a Zaddress 408) and a Y address 406. In some embodiments, an exposure image(also known as an exposure map) can include a large array t_(ik), orN_(ik), where N is the number of pulses, and (i, k) is a node of thearray with (x_(i), y_(k)) coordinate of the (i, k)'s where the addressidentified in the exposure image corresponds with an address of a cellof the set of plasma elements 400A-B. For example, an address in theimage file may contain data indicative of a time duration or exposureduration an associated addressable node (or cell) is to activate duringa plasma process.

In some embodiments, to convert exposure image t_(ik) to addressingimage, normalization can be used to a process time t_(pr), color, orgray shade as in

$\begin{matrix}{t_{pr} = {\max\left( t_{ik} \right)}} & {{Equation}\mspace{14mu} 1} \\{\tau_{ik} = \frac{t_{ik}}{t_{pr}}} & {{Equation}\mspace{14mu} 2}\end{matrix}$

By multiplying τ_(ik) by the number of grey levels N_(G) and taking theinteger part of the result (mod 1) yields Grey Level (GL)

GL _(ik)=(N _(G)τ_(ik))mod 1  Equation 3

GL_(ik) is the addressing image of the exposure image τ_(ik). To use itin addressing, GL_(ik) values can be converted into N_(sf)-bit numbers,where each bit displays whether the cell is addressed on or off for aparticular subfield. For example, for the 8-subfield addressing(N_(sf)=8), with each subfield proportional to 2^(k-1) starting from 1,the number 01010101 means level 170 (out of 255) and the cell isaddressed ON during subfields number 2, 4, 6, 8, and OFF for the rest ofthe subfields.

FIG. 5 illustrates a digital process control system 500, according toaspects of the disclosure. The digital process control system 500 may beused in association with or as a part of a plasma control plate (e.g.,control plate 304 of FIG. 3). The digital process control system maycontrol power and/or voltage delivery to digital process elements 508(e.g. bias electrodes FIG. 3, etc.). Digital process control system 500may be designed to selectively turn on and off the individual digitalprocess elements 508. The digital process system 500 may include anelectrostatic chuck (ESC) 502, a switch controller 504 including a setof switches 510, and an RF generator (RFG) with matching circuitry (alsoknown as a match) 506. The digital process control system 500 maycontrol activation time of digital process elements 508. The activationtime of the digital process elements 508 includes energizing any digitalprocess element k (or i, k for two-dimensions (2D)) for a specific timet_(k) independently of all other elements.

For example, any time t_(k) (or t_(ik) for 2D array) as a sumt_(k)=t_(min)+Δ t_(k) (or t_(ik)=t_(min)+Δt_(ik)), where t_(min) is theshortest of all t_(k) (or t_(ik)) and 0≤Δt_(k)≤Δt_(max), whereΔt_(max)=t_(max)−t_(min). This split may allow precise control of timeindependent of the total time. The time resolution is applied to therelatively short time Δt_(max), which is usually much smaller thant_(max). It is convenient to choose precision δt with which this time iscontrolled, so that the difference between any actual t_(k) is largerthan δt. In this case the potential

$N_{G} = {\frac{\Delta t_{m\;{ax}}}{\delta t}.}$

number of gray scale level, that defines the precision of the timecontrol is that δt can be used for a brief duration (e.g., as short as amillisecond, or even shorter). This can be achieved by the followingembodiments.

In a system having bias electrodes (e.g., electrodes 302A-C and 304A-Cof FIGS. 3A-B), where the bias electrodes are driven with a single fixedbias voltage RF generator 506, switch controller 504 may store timevalues t₁, t₂, . . . , t_(N) with resolution δt and group the switches(each group has the same time on) and when the time comes, turns off thecontact (switches 510) between RF generator 506 and the digital processelements 508. If necessary, the switch controller 504 may send a signalto the RF generator indicating that the power must be reduced by aspecific value related to the number of digital process elements turnedon or off at that moment. Note that every switch 510 may control arelatively small power/current, if the number of digital processelements is large and the time required to turn off a switch 510 or agroup of switches is very short.

In another embodiment, in a system having a Dielectric Barrier Discharge(DBD) based plasma source similar to discharge cell described inassociated with FIG. 2, all DBD cells can be driven with exactly thesame meander like sustain voltage waveform, but the discharge will begenerated only in cells previously selected (addressed). The time can bedivided Δt_(max)=t_(max)−t_(min) in a number of subfields. For example,with the time length of each subfield

$\frac{\Delta t_{m\; a\; x}}{2^{m}},$

where m∈(1, M) is the subfield number, so that combining subfield timescan make any time t with precision

${\delta\; t} = {\frac{\Delta t_{m\;{ax}}}{2^{M}}.}$

Erasing all cells (e.g. turning them all off) and then addressing cellsbetween subfield can generate an image for any particular subfield. Thewhole discharge will contain an “all on” image for time t_(min),followed by M corrective images. The overall image represents the arrayt_(ik) for generating discharge in the array source with precision

$\frac{t_{m\;{ax}} - t_{m\; i\; n}}{2^{M}}.$

For example, if the total process time is 100 seconds and the maximumcorrection required for the process is 10 seconds (10%), with only 6subfield in total (M=5), the precision of the process control will be0.3 second, or 0.3%.

In some embodiments, the exposure distribution image may be associatedwith or correspond to a process result image h(k), where colors areassigned based on the relative change of the film thickness, as will bediscussed in associated with FIG. 6B.

FIG. 6A-E illustrates various images, illustrating a process flowaccording to aspects of the disclosure. For example, FIG. 6A illustratesan initial choice of a uniform exposure image for achieving a uniformtarget process image. This image has number of elements equal to thenumber of controlled elements, which we expect to be large, so we callit High Resolution (HR) exposure image. FIG. 6B illustrates an exampleof a non-uniform Low Resolution (LR) process image obtained in theresult of exposure image 6A, and obtained using metrology tool after theprocess is complete. Typical number of elements in this LR image is 49,and values in between these measured points are result of interpolation.FIG. 6C illustrate the same LR process image (with e.g. 49 elements)converted to a High Resolution process image (e.g. 1000 elements), whereeach element has coordinates of the controlled elements. FIG. 6Dillustrates a corrected exposure image, obtained using a simpleprocedure described in this invention. FIG. 6E illustrates a resultinguniform HR process result image.

Typical process results, as shown in FIG. 6B, are indicative of ameasured parameter (e.g. such as film thickness of a substrate) changeas a result of the process. The parameter can be measured over multiplepoints (e.g., 49 points). Alternatively, more or less points can be usedto measure the parameter. The measured points and their locations maynot be related to positions and a number of controlled elements, asshown in FIGS. 6A, 6C, and 6D, that are being addressed. The raw processresult image h_(raw)(x, y) h_(raw)(k; k=1-49), as seen in FIG. 6B, canbe converted into a processing image (e.g., FIG. 6C) with sourcescoordinates h_(ik), =h(x_(i), y_(k)). To perform this conversion, thecontrol unit interpolates h_(raw)(x, y) an area of the process resultimage, including outside of the wafer, and extracts data h_(ik), relatedto the source coordinates (x_(i), y_(k)) from this interpolation. Thisarray h_(ik), =h(x_(i), y_(k)) is the process result image (e.g., FIG.6C or a corrected exposure image FIG. 6D), which a processing unit (e.g.processing unit 207 of FIG. 2) uses for generating the exposure imaget_(ik)=t(x_(i), y_(k)) (e.g., FIG. 6E). In some embodiments, theexposure image can include 2D arrays images where any one of them can berepresented as product of maximum value (brightness) and the relativevalue−ratio of the local value to the maximum (a “color” or “shade”)

$\begin{matrix}{{h_{ik} = {h_{{ma}\; x}\frac{h_{ik}}{h_{m\;{ax}}}}},{t_{ik} = {t_{m\;{ax}}\frac{t_{ik}}{t_{m\;{ax}}}}},} & {{Equation}\mspace{14mu} 4}\end{matrix}$

For example, the data can be illustrated or “painted” by placing aproper color in the positions (x_(i), y_(k)).

In some embodiments, the exposure images can be tuned and improvedthrough image processing. For example, a process can start with aprocess image obtained from an arbitrary initial exposure distributionimage (e.g. FIG. 6C) and then using a standard procedure with a simplenumerical algorithm one can correct elements of the exposure image arrayassociated with the process image array. The corrected image (e.g., FIG.6D) can be applied to obtain a process image (e.g., FIG. 6E) closer tothe desired process result (image) (DPI) than the initial image (e.g.,FIG. 6B). This can be repeated until the difference between the desiredprocess image (DPI) and actual process image (PI) is satisfactory (e.g.meet a threshold or target thickness profile).

FIG. 7 illustrates a digitally controlled plasma processing device,according to the present disclosure. FIG. 7A illustrates an actuatorplate 700A, FIG. 7B depicts a selection of plasma cells 700B, and FIG.7C depicts a control unit 700C of a digitally controlled plasmaprocessing device. In one embodiment, the plasma processing devicedepicted in FIGS. 7A-C may include any of the plasma processing systemsdisclosed in any of FIGS. 1-6. Alternatively, the plasma processingdevice may be other plasma processing devices, as described herein.

As seen in FIG. 7A, actuator plate 700A includes multiple interfaces702A-C. For example, three interfaces may be used (e.g. an X-interface702A, a Y-interface 702B, and a Z-interface 702C). Each interface mayinclude a series of leads (e.g. wires) that are coupled to a set ofplasma cells 706 disposed across the actuator panel 700A. It should benoted that the relative orientation of each interface is exemplary, andthe role each interface 702A-C carries out is interchangeable with theother interfaces. In some embodiments, a first interface (e.g., Zinterface) carries, during an addressing period of a plasma process, anaddressing signal to address (e.g. digitally flag, electronically storedata) a selection of plasma cells 706 that are to be activated during anupcoming sustain period of the plasma process. A second and thirdinterface (e.g. x interface 702A and y-interface 702B) carry a sustainsignal to each of the plasma cells 706 during the sustain period of theplasma process. The addressing signal can be targeted to a selection ofcells. In some embodiments, the sustain signal is carried to each plasmacell 706, regardless of whether they have been previously addressed.However, in other embodiments, a selection of cells (e.g. only theaddressed cells, “ON” cell) receive a sustain signal.

As shown in FIG. 7B, plasma cells 706 may include an addressable switch(i.e. addressable actuator) 710, a memory element 712, and an emitter714. In some embodiments, the memory element 712, which may correspondto any combination of volatile and/or non-volatile storage mechanisms,receives an addressing signal (e.g. from Z interface 702C and Yinterface 702B) and stores in memory an indication the cell has beenaddressed (e.g. during and addressing period of a plasma process). Theplasma cell 706 can receive a sustain signal (e.g. from X interfaces702A and Y interface 702B). If the plasma cell 706 had previously beenaddressed by an addressing signal, the indication in the memory element712 causes the addressable switch to close. The closing of theaddressable switch allows the sustain signal to activate the emitter714. The emitter may include a light emitter, a plasma generator (e.g.ion or electron fluxes), or a plasma shutter. For example, the emitter714, when activated, can generate and emits plasma related fluxes.

As shown in FIG. 7C, the process of addressing and sustaining the plasmacells can be carried out by a control unit 700C. Control unit 700C caninclude one or more processor(s), analyzer(s), and/or circuitry toaddress and sustain the plasma cell 706. As seen in FIG. 7C, the controlunit 700C includes a process step analyzer 720. The process stepanalyzer 720 receives configuration and/or parameter data for a processstep in a plasma process. For example, the process step analyzer canreceive gas information (e.g. type of gas, flow rate of gas, pressure ofgas, etc.), pressure of the processing chamber, total process time ofthe process step, energy requirements (e.g. ion energy for biaselectrodes). The control unit also includes a generator 722. Thegenerator 722 may include a DC generator and/or and RF generator. Thegenerator 722 coordinates with the process step analyzer 720 to generatea required base signal with required amplitudes (e.g., auxiliary signalrequired for control or address (e.g. control signals), and othervoltage magnitudes and process times to carry out the process step). Forexample, the process analyzer 720 may determine an addressing voltage, asustain voltage, a scanning voltage as well as determine how to split atotal process time into an addressing duration, a scanning duration, anda sustain duration. In some embodiments, as described in detail in otherembodiments, the process step may be performed using multiple subfields.The duration of each subfield may be determined by the process stepanalyzer 720 and carried out by generator 722.

As shown in FIG. 7C, the control unit 700C includes processing elements(e.g. processors) to carry out an image processing function 724 and aprocess tuning function 726, as will be discussed in later embodiments(e.g., method 800-1000 of FIGS. 8-10). In some embodiments the imageprocessing function 724, may include generating and addressing image andbreaking the addressing image into a series of subfield images to carryout the process step. In some embodiments, the process tuning function726 coverts actual measured image data (e.g. 49 measured points across asubstrate) into a process image with coordinates of plasma elements. Theprocess tuning function may further compare a desired process image withthe process image and generate a new addressing image with a newprocessing time and new subfield information (e.g. the length of eachsubfield). This new addressing image and associated data may then beused for the next iteration of the process step.

As shown in FIG. 7C, the control unit include drivers 728, 730 and asynchronizer 732. Driver 728 is associated with powering the plasma cellduring both the address and sustain period. Driver 730 is associatedwith powering a selection of plasma cells that are to be addressed basedon an addressing image. The synchronizer 732 coordinates the generatedsignals from each of the driver to carry out the addressing, scanning,and sustaining of the plasma cell 206. As previously described multipleinterfaces 702A-C are used to transmit the signal to the plasma cell 206on the actuator plate 700A. It should be noted that an ON state may be afirst voltage level and the OFF state can be a second voltage level. Forexample, the first voltage level may be greater than the second voltagelevel. In another example the second voltage level may be ground.

FIGS. 8-12 depict flow diagrams illustrating example methods 800-1200related to digital plasma process control, in accordance with someimplementations of the disclosure. For simplicity of explanation,methods 800-1200 are depicted and described as a series of acts.However, acts in accordance with this disclosure can occur in variousorders and/or concurrently and with other acts not presented anddescribed here. Furthermore, not all illustrate acts may be performed toimplement the methods 800-1200, in accordance with the disclosuresubject matter. In addition, those skilled in the art will understandand appreciate that methods 200-400 could alternatively be representedas a series of interrelated states via a state diagram or events.Methods 800-1200 may be performed, for example, by plasma processingsystems 100 or 200 of FIGS. 1-2. At least some operations of methods800-1200 are controlled and/or implemented by a controller of a processchamber, such as by control unit 700C of FIG. 7C.

FIG. 8 is a flow chart of a method 800 for plasma processing, accordingto aspects of the disclosure. Referring to FIG. 8, at block 801processing logic receives exposure data associated with carrying out aplasma process using digital process control. The exposure data can betransmitted as an exposure map (e.g. an image file, or an exposure mapas discussed in associated with FIG. 6A-B). Alternatively oradditionally, the exposure data may include plasma process parameterssuch as a sustain voltage, an addressing voltage, a total process time,and subfield structure (e.g. a number of subfields and relativeprocessing times), among other things.

At block 802, processing logic generates a set of subfields associatedwith the exposure data. The subfields can include plasma exposure valueseach associated with a respective plasma element of a set of plasmaelements configured to generate plasma related fluxes. For example,subfields as described in association with FIGS. 1A-C can be used todivide a total process time into frames and/or subframes.

At block 803, processing logic addresses a selection of plasma elementsassociated with a first subfield of the set of subfields. In someembodiments, addressing techniques as described in associated with FIGS.7A-C can be used to address the selection of plasma elements. Forexample, as discussed in associated with FIGS. 7A-C, the plasma elementsmay include a memory element (e.g. memory element 712 of FIG. 7B) thatis capable of storing data capable of closing a switch that activates anemitter, responsive to receiving a sustain voltage.

At block 804, processing logic applies power to the plasma elements fora sustain period corresponding to the first subfield. The sustain periodcan include a time duration where a constant voltage (e.g. a sustainvoltage) is applied to each of the plasma elements. For example, asdiscussed in associated with FIG. 7B, during a sustain period all of theplasma elements are supplied with the same sustain voltage and thosecells that have previously been addressed (e.g. data stored in a memoryelement) drive and activate the element (e.g. light emitter, a plasmaemitter, a plasma shutter, etc.). For example, a resulting process imagecreated from a selection of plasma emitter increases in “brightness”(e.g. thickness change) as the sustain duration increases.

At block 805, processing logic removes (e.g. erases) addressingassociated with the first subfield. All of the plasma elements that havepreviously been addressed can be cleared of any addressable data (e.g.clearing any charge and/or data stored in memory elements 712).

At block 806, processing logic addresses another selection of plasmaelements associated with the next subfield. As previously discussed,addressing techniques, as described in associated with FIGS. 7A-C can beused to address this next selection of plasma elements similar to theimplementation of the processing logic at block 803.

At block 807, processing logic applies power the plasma elements for asustain period corresponding to a subfield associated with thepreviously addressed plasma elements. As discussed previously, thesustain period can include a time duration where a constant voltage(e.g. a sustain voltage) is applied to each of the plasma elements. Forexample, as discussed in associated with FIG. 7B, during a sustainperiod all of the plasma elements are supplied with the sustain voltageand those cells that have previously been addressed (e.g. data stored ina memory element) drive and activation element (e.g. light emitter, aplasma emitter, a plasma shutter, etc.). For example, a resultingprocess image created from a selection of plasma emitter increases in“brightness” (e.g. thickness) as the sustain duration increases.

At block 808, processing logic removes addressing associated with thepreviously addressed selection of plasma elements. All of the plasmaelements that have previously been addressed can be cleared of anyaddressable data (e.g. clearing any charge and/or data stored in memoryelements 712), as similarly implemented at block 805.

At block 809, processing logic determines whether all subfields in theset of subfields have been processed. Responsive to determining that allsubfields have been processed, processing logic proceeds along the yespath to block 810. Responsive to determining that the all subfields inthe set of subfields have not been process, processing logic proceedsalong the no path to block 806 and proceeds with addressing a selectionof cells associated with the next subfield.

At block 810, processing logic determine whether all frames have beenprocessed. Responsive to determining that all frames have beenprocessed, processing logic proceeds along the yes path and ends.Responsive to determining that all frames have not been processed,processing logic proceeds along the no path to block 803 and proceedswith processing the next frame. In some embodiments this process isrepeated for until all subfields have been process, however, in otherembodiments the process continues until an end condition of the plasmaprocess is met (e.g. a process result meets a threshold criterion).

In some embodiments, the method 800 is repeated many times (M), usingframes, gradually making the images (both exposure and process images)“brighter.” Each frame uses the same image (t₁τ_(ik)) resulting in thesame normalized process image as H_(ik), but the “brightness” h_(ik),grows with the number of frames until it reaches H_(ik). The processtime is the sum of the displaying a single frame t₁, T=Mt₁. For example,for a uniform desired process image (DPI), H_(ik)=H=const, the singleframe process image h_(ik), will also be uniform, and time will increasethe “brightness”/thickness of the same image.

In another embodiment, the exposure image is displayed only once, butthe whole process time is divided based on the proper number ofsubfields and each subfield is effectively M times longer than theappropriate subfield in the previous embodiment. In this embodiment,some areas reach H_(ik) earlier, and then stop, while the other areasare still processed until the whole image reach desiredbrightness/thickness values. For example, for a uniform DPIH_(ik)=H=const, the image will not be uniform until the very end, whenarea one by one stop changing their brightness until the last onereaches the same value.

FIG. 9 is a flow chart of a method 900 for tuning a plasma process,according to aspects of the disclosure. Referring to FIG. 9, at block901, processing logic receives data including a set of plasma exposuredurations associated with a set of plasma elements. In some embodiments,the data is received in the form of an exposure image comprising“brightness” values that correspond with exposure duration for each ofthe plasma elements. For example, the plasma elements can be representedas nodes (i, k) indicative of their relative location to each other andthe exposure image may comprises values (e.g. depicted as color orvarying degrees of brightness) that map to individual plasma elementsand correspond to a total exposure duration for each plasma elements.

At block 902, processing logic performs a process on a substrate using aset of plasma exposure durations with the set of plasma elements. Theplasma elements may be configured to generate plasma related fluxes. Insome embodiments, the set of plasma exposure durations include an amountof time t_(ik) an associated plasma element exposes the first substrateto the plasma related fluxes generated by the associated plasmaelements. In other embodiments, the first data further include a processtime duration indicative of a total amount of time to perform asubstrate process operation on the first substrate. Any of the set ofplasma exposure durations may include a percentage value of the processtime duration. In some embodiments, the set of plasma exposure durationinclude a quantity of plasma pulses N_(ik) an associated plasma element(i, k) exposes the first substrate to during a plasma process. In someembodiments, as described in detail in association with other figures(e.g., FIG. 9), the substrate processing may be performed in a singleframe or multiple frames having a varying number of subfields.

As previously noted, in some embodiments, the first data may be storedas an image file (e.g., {dot over (h)}_(ik) ≡δh_(ik)/δt). The set ofplasma exposure durations may be stored as an array or map having atleast one of brightness value or color values indicative of the exposureduration. Processing the data may include converting the image file toand addressing image. For example, the color map may be indicative ofthe general exposure that get converted to an addressing image or datathat is mapped to show individual exposure duration of the set of plasmaelements. This data can be stored as an entire frame or divided intosubfields and addressed, sustained, and erased (e.g. as described inmethod 800 of FIG. 8).

In some embodiments, the data received is in the form of an exposureimage, t(x, y) on a substrate through an image file or exposure map. Forexample, for digitally controlled multiple sources/plasma elements theprocess result thickness (growth film, etch depth, etc.) is a functionof space and time h(x_(i), y_(k), t)≡h_(ik) (t), where t=t(i, k)=t_(ik)is the ON time for the source positioned in the (i, k) node. Using file{dot over (h)}_(ik)≡dh_(ik)/dt and the fact that

${\frac{\delta{h}}{\delta t} > 0},$

the exposure time t_(ik) can be adjusted in every node (i, k) to achievethe process profile h₀ (x, y). This time t_(ik) is an exposure imagethat can constitute the data to be received at block 901.

At block 903, processing logic receives data comprising the set ofplasma exposure durations and the associated thickness profile of thesubstrate generated using the set of plasma exposure durations with theset of plasma elements. In some embodiments, the thickness profile mayinclude a thickness of a film taken in a few points measured across thesubstrate (e.g. 49 locations across the substrate). The thicknessprofile may then be extrapolated to represent the thickness across thesurface of the substrate in areas not disposed away from the measuredlocations. The thickness profile, or on-wafer result image, can includethe process result (e.g. thickness of grown film, etch depth, etc.) as afunction of coordinate h(r) interpolated to positions of the plasmaelements (e.g. plasma mini-sources) r_(ik): h(r_(ik))=h (x_(i),y_(k))≡h_(ik). Independently of the position and number of actualmeasurement points, the dimension and coordinate of the process imagearray are the same as of the exposure image array t(r_(ik))=t_(ik).

The thickness h_(ik)(t) around a plasma element (also known as a node)grows with time on (or number of pulses in DBD) in that node (i, k) toachieve the desired process image (DPI) H(x, y). The time t_(ik) is theaddressing image we are looking for to obtain the on-wafer image h_(ik),=H_(ik).

At block 904, processing logic determines an update to the set of plasmaexposure durations based on a comparison between the associatedthickness profile and a target thickness profile. For example, acomparison can be drawn between the thickness profile h_(ik)=k(t_(ik))with and the target thickness profile or DPI H_(ik). Updates to varioustime durations t_(ik) or quantity of plasma pulses N_(ik) can be updatedfor the individual plasma elements (i, k).

At block 905, processing logic performs the process on a new substrateusing the updated set of plasma exposure durations with the set ofplasma elements. In some embodiments, the process may be performed usingthe same equipment (e.g. plasma elements) with only the exposuredurations changed.

At block 906, processing logic receives data including the associatedthickness profile of the new substrate generated using the updated setof plasma exposure durations with the set of plasma elements. Thethickness profile receive in block 906 may include the same features asthe thickness profile received in block 903.

At block 907, processing logic determines whether the associatedthickness profile of the new substrate satisfies a criterion. Responsiveto determining that the associated thickness profile of the newsubstrate profile does satisfy a criterion, processing logic proceedsalong the yes path to block 908. Responsive to determining that theassociated thickness profile of the new substrate profile does notsatisfy a criterion, processing logic proceeds along the no path toblock 904. In some embodiments, the thickness profile h_(ik), maysatisfy the threshold criterion when the difference between h_(ik) anddesired process image (DPI) (H_(ik)) is within a threshold criterion.For example, each thickness value of the profile may be within apredetermined difference limits, process control limit, and/orstatistical boundary.

At block 908, processing logic save (e.g., stores locally) the new imagefile and ends the process.

In some embodiments, tuning is used for updating the total time (e.g.brightness) of the same image, in some embodiments tuning is used toupdate the image, keeping the same total time, and in some embodiments,both the total time and image may be updated. For example tuning thetotal time or updating the image may be used to update a process that ispartially developed or stable. For example, updating a portion of thedata (e.g. brightness or image file) may apply fine adjusting such asaccounting for slow process drift during normal fabrication operations.In this embodiments, a test wafer can be used.

In some embodiments, measuring of the substrate (e.g. determine thethickness profiles that are received at blocks 903 and 905) may beperformed after a processing step is completed. For example the processresult (e.g., thickness profile change) may be ascertained outside of aprocessing chamber or location proximate a plasma source. However, inother embodiments techniques for in-situ process development can be usedto make on-demand adjustments to a fabrication process. For example, aspecific location on a substrate may be monitored live to activelydetermine any process updates to meet a desired outcome (e.g. processimage) at the monitored location of the substrate.

In some embodiments the initial address image is unknown, thus the totalprocess time t_(pr) is unknown. A uniform address image (t(i, k)=t_(pr))can be used as a starting point (e.g. at block 901 and 902).

FIG. 10 is a flow chart of a method 1000 for tuning a plasma process,according to aspects of the disclosure. Method 1000 may include,generally, processing multiple wafers (e.g., two wafers at a time) usinga variety of time durations and drawing a comparison between theresulting thicknesses determine a rate of thickness value change for oneor more processing locations on a first substrate and a second substratebased on the. A modification to the processing instructions (e.g., imagefile) can be determined based on the rate of the thickness value change.For example, modifying of the first data may be responsive todetermining that the rate of thickness value change of one or moreprocessing locations meets a threshold value.

The following embodiment is an example process of using method 1000 totune plasma exposure duration (e.g. an exposure image). At block 1001,processing logic receives an arbitrary initial image file t_(ik)=t_(ik)⁰. At block 1002, processing logic processes two substrates (e.g.wafers)—one with time t_(ik), and the other with time t_(ik)+δt. In someembodiments, the initial image t_(ik) ⁰. can be a simple uniform image(e.g. a uniform grey image) where all elements are the same, or createdpreviously for a similar process, and δt (e.g. an update to the set ofplasma exposure durations) can be the same for every node and should bea few percent of the process t_(pr).

At block 1003, processing logic compares a first thickness profileassociated with the first substrate with a second thickness profileassociated with the second substrate. In some embodiments, the thicknessprofile can be represented generally as process images (e.g. a mappingof the thickness across each substrate). For example, the process imageson these wafer can be represented as:

h _(ik) =h _(ik)(t _(ik))  Equation 5

and

h _(ik)(t _(ik) +δt)=h _(ik) +δh _(ik)  Equation 6

At block 1004, processing logic determines a film growth rate (or moregenerally a rate of thickness value change). The film growth rate can beassociated with the plasma elements (e.g. disposition of the elements,type of elements, processing chamber parameters, etc.). For example,using the Equations 5 and 6, the following growth rate file (array) canbe obtained using the following:

$\begin{matrix}{{\overset{.}{h}}_{ik} = \frac{\delta h_{ik}}{\delta t}} & {{Equation}\mspace{14mu} 7}\end{matrix}$

A comparison can be drawn between the thickness profile h_(ik),=h(t_(ik)) with the target thickness profile or DPI H_(ik) (e.g. atblock 1003).

At block 1005, processing logic determines whether the first thicknessprofile of the associated substrate satisfies a criterion. Responsive todetermining that the associated thickness profile of the new substrateprofile does satisfy a criterion, processing logic proceeds along theyes path to block 1007. Responsive to determining that the associatedthickness profile of the new substrate profile does not satisfy acriterion, processing logic proceeds along the no path to block 1006. Insome embodiments, the thickness profile h_(ik) may satisfy the thresholdcriterion when the difference between h_(ik) and desired process image(DPI) (H_(ik)) is within a threshold criterion. For example, eachthickness value of the profile may be within a predetermined differencelimits, process control limit, and/or statistical boundary.

At block 1006, processing logic updates the image file based on the filmgrowth rate. Updating the image file may include updating the set ofplasma exposure duration. Updating the set of plasma exposure durationsmay include correcting the initial process image using the following:

$\begin{matrix}{\left. t_{ik}\rightarrow{t_{ik} + \frac{H_{ik} - h_{ik}}{{\overset{.}{h}}_{ik}}} \right. = {t_{ik} + {\frac{H_{ik} - h_{ik}}{\delta h_{ik}}\delta\; t}}} & {{Equation}\mspace{14mu} 8}\end{matrix}$

And repeating the image processing procedures (e.g. blocks 1002, 1003,1004):

t _(ik) →h _(ik) ,{dot over (h)} _(ik)→CHECK→δt(i,k)→t(i,k)

until the difference between h_(ik) and DPI (H_(ik)) is within athreshold criterion (e.g. at block 1005).

At block 1007, processing logic save the image file and/or growth ratefile and ends the process.

FIG. 11 is an exemplary illustration of a training phase of a machinelearning model, according to aspects of the disclosure. A system such asa machine learning system may use method 1000 to at least one of train,validate, or test a machine learning model, in accordance withembodiments of the disclosure. In some embodiments, one or moreoperations of method 1000 may be performed by a data set generator of acomputing device (e.g., computing device 730 of FIG. 7). It may be notedthat components described with respect to FIG. 1-7 may be used toillustrate aspects of FIG. 11. In some embodiments, machine learning isperformed to determine the interaction between plasma elements of adigital plasma system and how changes in how long a particular plasmaelement is active (or open) affects both a region of a substrate that isassociated with that particular plasma element as well as regions of thesubstrate that are proximate to the region associated with theparticular plasma element. For example, the ON time for a plasma elementmay most strongly impact a region of a substrate that is directly underthat plasma element. However, the ON time for that plasma element mayalso affect regions that are not directly under the plasma element butthat are around the region that is directly under the plasma element. Asa result, increasing or decreasing the ON time for a particular plasmaelement has effects on multiple regions of a substrate. Thus, when afirst plasma element ON time is reduced to lower an amount of plasmaflux that reaches a particular region, this may also reduce the amountof plasma flux that reaches surrounding regions, and thus it may beappropriate to also increase the ON time for one or more other plasmaelements associated with the surrounding regions. However, such changein those plasma elements may increase a flux on still other regions,which may warrant changing the ON time of still other plasma elementsassociated with those regions. Accordingly, in embodiments a model isgenerated that can be used to determine what adjustments to make to arecipe run on a particular process chamber based on a thickness profileof a substrate processed on the process chamber.

Referring to FIG. 11, in some embodiments, at block 1101 the processinglogic implements method 1100 and initializes a training set T to anempty set.

At block 1102, processing logic identifies a first data input (e.g.first training input, first validating input) that includes a thicknessprofile of a substrate. The first data input may include a thicknessprofile including one or more thickness values of film on a substratemeasured at various location across a surface of the substrate.

At block 1103, processing logic identifies a first target output for oneor more of the data inputs (e.g., first data input). The first targetoutput includes an exposure map (e.g. image file or exposure durationdata) that when processed by a plasma delivery system results in thethickness profile used as the first target input.

At block 1104, processing logic optionally generates mapping data thatis indicative of an input/output mapping. The input/output mapping (ormapping data) may refer to the data input (e.g., one or more of the datainputs described herein), the target output for the data input (e.g. oneor more of the data inputs described herein), the target output for thedata (e.g. where the target output identifies an exposure map and/orimage), and an association between the data input(s) and the targetoutput.

At block 1105, processing logic adds the mapping data generated at block1104 to data set T.

At block 1106, processing logic branches based on whether the data set Tis sufficient for at least one of training, validating, or testing amachine learning model. If so (“yes” branch), execution proceeds toblock 1107, otherwise (“no” branch), execution continues back at block1102. It should be noted that in some embodiments, the sufficiency ofdata set T may be determined based simply on the number of input/outputmappings and/or the number of labeled exposure maps in the data set,while in some other embodiments, the sufficiency of data set T may bedetermined based on one or more other criteria (e.g., a measure ofdiversity of the data examples, accuracy, etc.) in addition to, orinstead of, the number of input/output mappings.

At block 1107, processing logic provides data set T to train, validate,or test machine learning model. In some embodiments, data set T is atraining set and is provided to a training engine to perform thetraining. In some embodiments, data set T is a validation set and isprovided to a validation engine to perform the validating. In someembodiments, data set T is a testing set and is provided to a testingengine to perform the testing. In the case of a neural network, forexample, input values of a given input/output mapping (e.g., numericalvalues associated with data inputs) are input to the neural network, andoutput values (e.g., numerical values associated with target outputs) ofthe input/output mapping are stored in the output nodes of the neuralnetwork. The connection weights in the neural network are then adjustedin accordance with a learning algorithm (e.g., back propagation, etc.),and the procedure is repeated for the other input/output mappings indata set T. After block 1107, a machine learning model can be at leastone of trained using a training engine, validated using a validatingengine, or tested using a testing engine. The trained machine learningmodel may be implemented by a control plate (e.g. control plate 106,204) and/or a computing device (e.g. computing device 730 of FIG. 7) toidentify an exposure map for a target thickness profile for a substrate.

In embodiments, a training dataset that was generated (e.g., asgenerated according to method 1100) is used to train a machine learningmodel and/or a physical model. The model may be trained to receive as aninput a thickness profile or thickness map as measured from a substratethat was processed by a process chamber using a plasma process and/or anexposure map of exposure settings for plasma elements of the processchamber that were used during the process that resulted in the thicknessprofile or thickness map that was generated. The model may output anexposure map (e.g., an updated exposure map) that indicates exposuresettings to use for each plasma element for future iterations of theprocess on the process chamber. In embodiments, the model may beagnostic to process chambers and/or to process recipes. Accordingly, themodel may be generated based on training data items generated based onprocesses run on a first process chamber or first set of processchambers, and may then be used for a second process chamber withoutperforming any transfer learning to tune the model for the secondprocess chamber. Once the model is generated, any thickness profileand/or exposure map may be input into the model regardless of whichspecific process chamber was used to perform a process that resulted inthe thickness profile, and the model may output an exposure map thatindicates which plasma element settings to use to result in a uniformplasma etch and/or a uniform plasma-enhanced deposition. The exposuremap may be input into a process chamber along with a process recipe, andthe process chamber may execute the process recipe with adjustmentsbased on the exposure map. For example, the exposure map may indicate,for each plasma element of a digital plasma source, what percentage of atime set forth in the recipe that the plasma element should be on oropen during the process.

In one embodiment, the trained machine learning model is a regressionmodel trained using regression. Examples of regression models areregression models trained using linear regression or Gaussianregression. A regression model predicts a value of Y given known valuesof X variables. The regression model may be trained using regressionanalysis, which may include interpolation and/or extrapolation. In oneembodiment, parameters of the regression model are estimated using leastsquares. Alternatively, Bayesian linear regression, percentageregression, leas absolute deviations, nonparametric regression, scenariooptimization and/or distance metric learning may be performed to trainthe regression model.

In one embodiment, the trained machine learning model is a decisiontree, a random forest model, a support vector machine, or other type ofmachine learning model.

In one embodiment, the trained machine learning model is an artificialneural network (also referred to simply as a neural network). Theartificial neural network may be, for example, a convolutional neuralnetwork (CNN) or a deep neural network. In one embodiment, processinglogic performs supervised machine learning to train the neural network.

Artificial neural networks generally include a feature representationcomponent with a classifier or regression layers that map features to atarget output space. A convolutional neural network (CNN), for example,hosts multiple layers of convolutional filters. Pooling is performed,and non-linearities may be addressed, at lower layers, on top of which amulti-layer perceptron is commonly appended, mapping top layer featuresextracted by the convolutional layers to decisions (e.g. classificationoutputs). The neural network may be a deep network with multiple hiddenlayers or a shallow network with zero or a few (e.g., 1-2) hiddenlayers. Deep learning is a class of machine learning algorithms that usea cascade of multiple layers of nonlinear processing units for featureextraction and transformation. Each successive layer uses the outputfrom the previous layer as input. Neural networks may learn in asupervised (e.g., classification) and/or unsupervised (e.g., patternanalysis) manner. Some neural networks (e.g., such as deep neuralnetworks) include a hierarchy of layers, where the different layerslearn different levels of representations that correspond to differentlevels of abstraction. In deep learning, each level learns to transformits input data into a slightly more abstract and compositerepresentation.

Training of a neural network may be achieved in a supervised learningmanner, which involves feeding a training dataset consisting of labeledinputs through the network, observing its outputs, defining an error (bymeasuring the difference between the outputs and the label values), andusing techniques such as deep gradient descent and backpropagation totune the weights of the network across all its layers and nodes suchthat the error is minimized. In many applications, repeating thisprocess across the many labeled inputs in the training dataset yields anetwork that can produce correct output when presented with inputs thatare different than the ones present in the training dataset. Inhigh-dimensional settings, such as large images, this generalization isachieved when a sufficiently large and diverse training dataset is madeavailable.

The trained machine learning model may be periodically or continuouslyretrained to achieve continuous learning and improvement of the trainedmachine learning model. The model may generate an output based on aninput, an action may be performed based on the output, and a result ofthe action may be measured. In some instances the result of the actionis measured within seconds or minutes, and in some instances it takeslonger to measure the result of the action. For example, one or moreadditional processes may be performed before a result of the action canbe measured. The action and the result of the action may indicatewhether the output was a correct output and/or a difference between whatthe output should have been and what the output was. Accordingly, theaction and the result of the action may be used to determine a targetoutput that can be used as a label for the sensor measurements. Once theresult of the action is determined, the input (e.g., thickness profile),the output of the trained machine learning model (e.g., exposure map),and the target result (e.g., target thickness profile) actual measuredresult (e.g., measured thickness profile) may be used to generate a newtraining data item. The new training data item may then be used tofurther train the trained machine learning model. This retrainingprocess may be performed on-tool on the controller of the processchamber in embodiments.

In some embodiments, training the machine learning model may result in adata base for predictive processing. For example, uniform addressing(t_(ik)=t_(m)→h_(ik)(t_(m))) and singular (one cell) or some localizedprofile addressing t_(ik)=t+δt_(ik)→δh_(ik)(t) with δt_(ik) localizedaround (i, k) on the background of some level h_(ik)(t), and t_(m). isthe training set.

In some embodiments, a first set of uniform input images t₁, t₂, . . .for a fixed condition can be used to generate a set of appropriateoutput and set of appropriate localized growth rates δh_(ik)/δt. Theseoutput can be tested to produce a selection of target process images. Ifthe address images result in process images close enough to targetprocess images (e.g., at block 1106) for a determined process range,then process logic may continue to generate other process conditions(e.g., other gases). Method 1100 may be repeated for multiple processingconditions. If the generated process image is not close (e.g. if theprocess is non-linear and {dot over (h)}_(ik) depends on h_(ik)), thenadditional training time may be added between elements of the originalset.

In another embodiments, previously measured thickness levels h_(ik) (t)and makes localized addressing δt_(ik).

FIG. 12 is a flow chart of a method 1200 of using a machine learningmodel to modify a plasma exposure process, according to aspects of thedisclosure. Referring to FIG. 12, at block 1201, processing logicperforms a plasma process using an exposure image (e.g. exposure map) togenerate a substrate with a first thickness profile. The exposure imagemay include brightness or color value indicative of exposure durationfor a set of plasma elements to exposure a substrate to plasma relatedfluxes.

In some embodiments, the exposure image is displayed (repeated) manytimes (M), using frames, gradually making it “brighter.” Each frame usesthe same image (t_(t)τ_(ik)) resulting in the same normalized processimage H_(ik), but the “brightness” grows with the number of frames untilit reaches H_(ik). The process time is the sum of the displaying asingle frame t₁, T=Mt₁. For example, for a uniform desired process image(DPI), H_(ik)=H=const, the single frame process image h_(ik), will alsobe uniform, and time will increase the “brightness”/thickness of thesame image.

In another embodiment, the exposure image is displayed only once, butthe whole process time is divided based on the proper number ofsubfields and each subfield is effectively M times longer than theappropriate subfield in the previous embodiment. In this embodiment,some areas reach H_(ik) earlier, and then stop, while the other areasare still processed until the whole image reach desiredbrightness/thickness values. For example, for a uniform DPIH_(ik)=H=const, the image will not be uniform until the very end, whenarea one by one stop changing their brightness until the last onereaches the same value.

In another embodiments, every step of a plasma process may becharacterized by a fixed time. The time may be replaced by a link to theexposure image, which controls the process time of each cell or plasmaelement that may have thousands of elements. The exposure image may bestored in a file such as a uniform matrix (all elements identical),which can easily be created manually, when no other files, exists, orvery complex and can utilized complex algorithms for the purpose ofobtaining a specific process image.

At block 1202, processing logic provides the thickness profile as inputto a trained machine learning model associated with a target thicknessprofile. The first thickness associated with process the exposure image.The machine learning model may be configured to reach a desired targetthickness profile. The target thickness profile may be associated withspecifications or properties of a substrate.

At block 1203, processing logic obtains output(s) from the machinelearning model including modification to the first exposure map. Themachine learning model may receive the first exposure map in variousformats. For example, the exposure map may be received by the machinelearning mode as a map, array, matrix, series of values etc. indicativeof plasma processing exposure instructions.

At block 1204, processing logic applies one or more of the modificationsto the exposure map to generate a modified exposure map. In someembodiments, the modifications to the exposure map include changing oneor more exposure duration values of the exposure map.

At block 1205, processing a substrate with the modified exposure map togenerate a substrate with the target thickness profile. In someembodiments, process the first substrate with the modified exposureimage generates a substrate with the target thickness profile. In otherembodiments, processing a second substrate prior to process with thefirst exposure map, results in the second substrate having the targetthickness profile.

FIG. 13 depicts a block diagram of an example computing device 1300capable of plasma delivery and/or processing, operating in accordancewith one or more aspects of the disclosure. In various illustrativeexamples, various components of the computing device 1300 may representvarious components of the control plate (e.g. control plate 106, 204,702 of FIGS. 1, 2, and 7), computing device (e.g. computing device 730of FIG. 7), the training engine, validation engine, and/or the testingengine described in association with FIG. 11.

Example computing device 1300 may be connected to other computer devicesin a LAN, an intranet, an extranet, and/or the Internet. Computingdevice 1300 may operate in the capacity of a server in a client-servernetwork environment. Computing device 1300 may be a personal computer(PC), a set-top box (STB), a server, a network router, switch or bridge,or any device capable of executing a set of instructions (sequential orotherwise) that specify actions to be taken by that device. Further,while only a single example computing device is illustrated, the term“computer” shall also be taken to include any collection of computersthat individually or jointly execute a set (or multiple sets) ofinstructions to perform any one or more of the methods discussed herein.

Example computing device 1300 may include a processing device 1302 (alsoreferred to as a processor or CPU), a main memory 1304 (e.g., read-onlymemory (ROM), flash memory, dynamic random access memory (DRAM) such assynchronous DRAM (SDRAM), etc.), a static memory 1306 (e.g., flashmemory, static random access memory (SRAM), etc.), and a secondarymemory (e.g., a data storage device 1318), which may communicate witheach other via a bus 1330.

Processing device 1302 represents one or more general-purpose processingdevices such as a microprocessor, central processing unit, or the like.More particularly, processing device 1302 may be a complex instructionset computing (CISC) microprocessor, reduced instruction set computing(RISC) microprocessor, very long instruction word (VLIW) microprocessor,processor implementing other instruction sets, or processorsimplementing a combination of instruction sets. Processing device 1302may also be one or more special-purpose processing devices such as anapplication specific integrated circuit (ASIC), a field programmablegate array (FPGA), a digital signal processor (DSP), network processor,or the like. In accordance with one or more aspects of the disclosure,processing device 1302 may be configured to execute instructionsimplementing methods 800-1200 illustrated in FIGS. 8-12.

Example computing device 1300 may further comprise a network interfacedevice 1308, which may be communicatively coupled to a network 1320.Example computing device 1300 may further comprise a video display 1310(e.g., a liquid crystal display (LCD), a touch screen, or a cathode raytube (CRT)), an alphanumeric input device 1312 (e.g., a keyboard), acursor control device 1314 (e.g., a mouse), and an acoustic signalgeneration device 1316 (e.g., a speaker).

Data storage device 1318 may include a machine-readable storage medium(or, more specifically, a non-transitory machine-readable storagemedium) 1328 on which is stored one or more sets of executableinstructions 1322. In accordance with one or more aspects of thedisclosure, executable instructions 1322 may comprise executableinstructions associated with executing methods 800-1200 illustrated inFIGS. 8-12.

Executable instructions 1322 may also reside, completely or at leastpartially, within main memory 1304 and/or within processing device 1302during execution thereof by example computing device 1300, main memory1304 and processing device 1302 also constituting computer-readablestorage media. Executable instructions 1322 may further be transmittedor received over a network via network interface device 1308.

While the computer-readable storage medium 1328 is shown in FIG. 13 as asingle medium, the term “computer-readable storage medium” should betaken to include a single medium or multiple media (e.g., a centralizedor distributed database, and/or associated caches and servers) thatstore the one or more sets of operating instructions. The term“computer-readable storage medium” shall also be taken to include anymedium that is capable of storing or encoding a set of instructions forexecution by the machine that cause the machine to perform any one ormore of the methods described herein. The term “computer-readablestorage medium” shall accordingly be taken to include, but not belimited to, solid-state memories, and optical and magnetic media.

Some portions of the detailed descriptions above are presented in termsof algorithms and symbolic representations of operations on data bitswithin a computer memory. These algorithmic descriptions andrepresentations are the means used by those skilled in the dataprocessing arts to most effectively convey the substance of their workto others skilled in the art. An algorithm is here, and generally,conceived to be a self-consistent sequence of steps leading to a desiredresult. The steps are those requiring physical manipulations of physicalquantities. Usually, though not necessarily, these quantities take theform of electrical or magnetic signals capable of being stored,transferred, combined, compared, and otherwise manipulated. It hasproven convenient at times, principally for reasons of common usage, torefer to these signals as bits, values, elements, symbols, characters,terms, numbers, or the like.

It should be borne in mind, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities. Unlessspecifically stated otherwise, as apparent from the followingdiscussion, it is appreciated that throughout the description,discussions utilizing terms such as “identifying,” “determining,”“storing,” “adjusting,” “causing,” “returning,” “comparing,” “creating,”“stopping,” “loading,” “copying,” “throwing,” “replacing,” “performing,”or the like, refer to the action and processes of a computer system, orsimilar electronic computing device, that manipulates and transformsdata represented as physical (electronic) quantities within the computersystem's registers and memories into other data similarly represented asphysical quantities within the computer system memories or registers orother such information storage, transmission or display devices.

Examples of the disclosure also relate to an apparatus for performingthe methods described herein. This apparatus may be speciallyconstructed for the required purposes, or it may be a general purposecomputer system selectively programmed by a computer program stored inthe computer system. Such a computer program may be stored in a computerreadable storage medium, such as, but not limited to, any type of diskincluding optical disks, compact disc read only memory (CD-ROMs), andmagnetic-optical disks, read-only memories (ROMs), random accessmemories (RAMs), erasable programmable read-only memory (EPROMs),electrically erasable programmable read-only memory (EEPROMs), magneticdisk storage media, optical storage media, flash memory devices, othertype of machine-accessible storage media, or any type of media suitablefor storing electronic instructions, each coupled to a computer systembus.

The methods and displays presented herein are not inherently related toany particular computer or other apparatus. Various general purposesystems may be used with programs in accordance with the teachingsherein, or it may prove convenient to construct a more specializedapparatus to perform the required method steps. The required structurefor a variety of these systems will appear as set forth in thedescription below. In addition, the scope of the disclosure is notlimited to any particular programming language. It will be appreciatedthat a variety of programming languages may be used to implement theteachings of the disclosure.

The preceding description sets forth numerous specific details such asexamples of specific systems, components, methods, and so forth, inorder to provide a good understanding of several embodiments of thedisclosure. It will be apparent to one skilled in the art, however, thatat least some embodiments of the disclosure may be practiced withoutthese specific details. In other instances, well-known components ormethods are not described in detail or are presented in simple blockdiagram format in order to avoid unnecessarily obscuring the disclosure.Thus, the specific details set forth are merely exemplary. Particularimplementations may vary from these exemplary details and still becontemplated to be within the scope of the disclosure.

Reference throughout this specification to “one embodiment” or “anembodiment” means that a particular feature, structure, orcharacteristic described in connection with the embodiment is includedin at least one embodiment. Thus, the appearances of the phrase “in oneembodiment” or “in an embodiment” in various places throughout thisspecification are not necessarily all referring to the same embodiment.In addition, the term “or” is intended to mean an inclusive “or” ratherthan an exclusive “or.” When the term “about” or “approximately” is usedherein, this is intended to mean that the nominal value presented isprecise within ±10%.

Although the operations of the methods herein are shown and described ina particular order, the order of the operations of each method may bealtered so that certain operations may be performed in an inverse orderor so that certain operation may be performed, at least in part,concurrently with other operations. In another embodiment, instructionsor sub-operations of distinct operations may be in an intermittentand/or alternating manner.

It is to be understood that the above description is intended to beillustrative, and not restrictive. Many other embodiments will beapparent to those of skill in the art upon reading and understanding theabove description. The scope of the disclosure should, therefore, bedetermined with reference to the appended claims, along with the fullscope of equivalents to which such claims are entitled.

What is claimed is:
 1. A method, comprising: receiving, by a processingdevice, data comprising a first plurality of exposure values eachassociated with a respective controlled element of a plurality ofcontrolled elements configured to expose a substrate to related fluxes;and causing, by the processing device, a controller to activate theplurality of controlled elements based on the data to expose thesubstrate to the related fluxes generated by the plurality of controlledelements during a plasma process, wherein each respective controlledelement of the plurality of controlled elements is activated for aduration based on a respective exposure value from the first pluralityof exposure values that is associated with the respective controlledelement.
 2. The method of claim 1, further comprising: receiving, by theprocessing device, a first low resolution (LR) process image associatedwith a measurement of the substrate; and converting, by the processingdevice, the first LR process image to a first high resolution (HR)process image associated with the plurality of controlled elements. 3.The method of claim 2, further comprising: receiving, by the processingdevice, second data comprising a second plurality of exposure valuesassociated with the controlled elements; causing, by the processingdevice, the controller to activate the plurality of controlled elementsbased on the second data to expose a second substrate to the relatedfluxes generated by the plurality of controlled elements during theplasma process, wherein each respective controlled element of theplurality of controlled elements is activated for a second durationbased on a respective plasma exposure values from the second pluralityof exposure values; receiving, by the processing device, a second LRprocess image indicative of a second measurement of the secondsubstrate; converting, by the processing device, the second LR processimage to a second HR process image associated with the controlledelements; and generating an HR process rate image based on a comparisonbetween the first HR process image and the second HR process image. 4.The method of claim 2, further comprising: receiving, by the processingdevice a process rate HR image file indicative of process rates inlocations of the substrate associated with each controlled element; andgenerating, by the processing device, an updated HR process image basedon the process rate HR image file and the first HR process image.
 5. Themethod of claim 1, wherein the plurality of controlled elements arearranged in a grid, wherein the data comprises a map, and wherein eachrespective exposure value from the map is associated with one of theplurality of controlled elements in the grid.
 6. The method of claim 1,wherein the plurality of controlled elements comprises one or more of aplasma source, a plasma shutter, a bias electrode, or a heat source. 7.A method comprising: receiving, by a processing device, first datacomprising a first plurality of plasma exposure durations eachassociated with a respective plasma element of a plurality of plasmaelements configured to generate plasma related fluxes; receiving, by theprocessing device, a first thickness profile of a first substrate, thefirst thickness profile comprising a first plurality of thickness valuesof the first substrate measured after exposing the first substrate tothe plasma related fluxes for respective plasma exposure durationsdefined in the first data; determining, by the processing device, thatthe first thickness profile comprises a first thickness value for afirst location on the first substrate associated with a first plasmaelement of the plurality of plasma elements that deviates from areference thickness value; and responsive to determining that the firstthickness profile comprises the first thickness value that deviates fromthe reference thickness value, modifying, by the processing device, thefirst data by changing a first plasma exposure duration of the pluralityof plasma exposure durations that is associated with the first plasmaelement.
 8. The method of claim 7, further comprising: receiving, by theprocessing device, a second thickness profile of a second substrate, thesecond thickness profile comprising a second plurality of thicknessvalues of the second substrate measured after exposing the secondsubstrate to the plasma related fluxes for the respective plasmaexposure durations defined in the modified first data; determining, bythe processing device, that the second thickness profile comprises asecond thickness value for a second location on the substrate associatedwith a second plasma element of the plurality of plasma elements thatdeviates from the reference thickness value; and responsive todetermining that the second thickness profile comprises the secondthickness value that deviates from the reference thickness value,further modifying, by the processing device, the modified first data bychanging a second plasma exposure duration of the plurality of plasmaexposure durations that is associated with the second plasma element. 9.The method of claim 7, further comprising: receiving, by the processingdevice, second data comprising a second plurality of plasma exposuredurations each associated with the plasma elements; receiving, by theprocessing device, a second thickness profile of a second substrate, thesecond thickness profile comprising a second plurality of thicknessvalues of the second substrate measured after exposing the secondsubstrate to the plasma related fluxes for the respective plasmaexposure durations defined in the second data; comparing the firstthickness profile to the second thickness profile; and determining arate of thickness value change for one or more processing locations onthe first substrate and the second substrate based on a comparisonbetween the first thickness profile and the second thickness profile,wherein modifying the first data is further responsive to determiningthat the rate of thickness value change of one of the one or moreprocessing locations meets a threshold value.
 10. The method of claim 7,wherein one of the plurality of plasma exposure durations comprises anamount of time associated plasma elements expose the first substrate tothe plasma related fluxes generated by the associated plasma elements.11. The method of claim 7, wherein the first data further comprises aprocess time duration indicative of a total amount of time to perform asubstrate process operation on the first substrate, wherein one of thefirst plurality of plasma exposure durations comprises a percentagevalue of the process time duration.
 12. The method of claim 7, whereinthe first plurality of plasma exposure durations comprises a quantity ofplasma pulses an associated plasma element exposes the first substrateto during a plasma process.
 13. The method of claim 7, wherein the firstdata is stored as an image file, wherein each of the plurality of plasmaexposure durations is stored as an array of at least one of brightnessvalues or color values.
 14. A system, comprising: a processing chamber;a plurality of plasma elements disposed within the processing chamber,the plurality of plasma elements configured to generate plasma relatedfluxes; a plasma controller communicatively coupled to the plurality ofplasma elements and configured to control the plurality of plasmaelements; and a processing device, communicatively coupled to the plasmacontroller, to: receive first data comprising a first plurality ofplasma exposure values each associated with a respective plasma elementof the plurality of plasma elements; and cause the plasma controller toactivate the plurality of plasma elements based on the first data toexpose a first substrate to the plasma related fluxes generated by theplurality of plasma elements during a plasma process, wherein eachrespective plasma element of the plurality of plasma elements isactivated for a duration based on a respective plasma exposure valuefrom the first plurality of plasma exposure values that is associatedwith the respective plasma element.
 15. The system of claim 14, whereinthe processing device is further to: measure a first thickness of afirst location of a film on the first substrate that is associated witha first plasma element during the plasma process; determine an updatedfirst duration for which the first plasma element is to be activatedbased on a difference between the first thickness and a target thicknessof the film; and determine an updated second duration for which a secondplasma element is to be activated based on the first thickness, thetarget thickness, the first plasma exposure value and a second plasmaexposure value.
 16. The system of claim 14, wherein the plurality ofplasma elements are arranged in a grid, wherein the first data comprisesa map, and wherein each respective plasma exposure value from the map isassociated with one of the plurality of plasma elements in the grid. 17.The system of claim 14, wherein the processing device is further to:receive first data comprising a first plurality of plasma exposuredurations each associated with a respective plasma element of aplurality of plasma elements configured to generate plasma relatedfluxes; receive a first thickness profile of a first substrate, thefirst thickness profile comprising a first plurality of thickness valuesof the first substrate measured after exposing the first substrate tothe plasma related fluxes for the respective plasma exposure durationsdefined in the first data; determine that the first thickness profilecomprises a first thickness value for a first location on the substrateassociated with a first plasma element of the plurality of plasmaelements that deviates from a reference thickness value; and responsiveto determining that the first thickness profile comprises the firstthickness value that deviates from the reference thickness value, modifythe first data by changing a first plasma exposure duration of theplurality of plasma exposure durations that is associated with the firstplasma element.
 18. The system of claim 17, wherein the processingdevice is further to: receive a second thickness profile of a secondsubstrate, the second thickness profile comprising a second plurality ofthickness values of the second substrate measured after exposing thesecond substrate to the plasma related fluxes for a respective plasmaexposure durations defined in the modified first data; determine thatthe second thickness profile comprises a second thickness value for asecond location on the substrate associated with a second plasma elementof the plurality of plasma elements that deviates from the referencethickness value; and responsive to determining that the second thicknessprofile comprises the second thickness value that deviates from thereference thickness value, further modify, by the processing device, themodified first data by changing a second plasma exposure duration of theplurality of plasma exposure durations that is associated with thesecond plasma element.
 19. The system of claim 14, wherein the plasmaelements comprise one or more independent plasma sources configured togenerate identical plasma related fluxes.
 20. The system of claim 19,wherein the one or more independent plasma sources comprise a dielectricbarrier discharge (DBD) cell.